Akademik Veri Yönetim Sistemi
UZALCBS 2022 Sempozyumu, Ankara, Türkiye, 17 - 19 Kasım 2022, sa.12850, ss.1-6
Various applications such as monitoring the changes on Earth’s surface caused by natural hazards, rapid urbanization, etc.,
disaster management, planning of urban areas and agricultural lands, monitoring of natural resources have increased the need
for up-to-date land cover maps and these maps must be produced with high temporal and spatial resolution. The data collection
method used in the production of these maps is determined by taking into account the parameters such as the size of the study area,
time and cost. For this purpose, the use of optical and radar satellite images, remote sensing techniques and artificial intelligence
algorithms appear with an increasing frequency in the literature. MAXAR Technologies, one of the very high resolution satellite
data providers, has started to offer images in High Definition (HD) format obtained from 30 cm Ground Sampling Distance (GSD)
using advanced image processing methods. In this study, it was aimed to produce land cover maps with a deep learning approach
using HD images of a selected study area. The defined classes were water surface, vegetation, asphalt, building, shade and open
areas. The results showed that HD images are useful in land cover map production studies in urban areas and high classification
accuracy can be obtained from the deep learning methods.